Despite recent advances in gastric cancer therapy, chemotherapy resistance and lack of methods for selecting combination regimens remain major problems. Organoids, which provide a culture system that more closely resembles tumor cell organization than traditional cell lines, can be established from surgical specimens with a high success rate and are widely used for drug sensitivity assays. In this study, we aimed to identify a novel biomarker for predicting multidrug resistance using gastric cancer organoids (GCOs). We evaluated 5-fluorouracil or oxaliplatin-resistant GCOs to find novel biomarkers that reflect multidrug resistance in gastric cancer. To examine the resistance mechanisms, RNA-sequencing analysis and ex vivo drug sensitivity testing were performed. The association of biomarkers with patient prognosis and chemotherapy efficacy was evaluated using three original cohorts with a total of 230 cases. The results were also validated with two independent public cohorts and single-cell RNA sequence data. Increased expression of peptidase inhibitor 3 (PI3) was detected in all 5-fluorouracil or oxaliplatin-resistant GCOs. Our findings suggest a potential association of PI3 expression with ribosome biosynthesis and RNA metabolism under organoid conditions. We also found that PI3 overexpression promoted 5-fluorouracil/oxaliplatin/cisplatin resistance but not paclitaxel resistance. Immunohistochemical evaluation of PI3 expression revealed that the PI3-positive gastric cancer group had a poorer outcome, especially in terms of time to recurrence. PI3 positivity was also an independent predictor of relapse after chemotherapy with DNA-damaging agents. PI3 promotes DNA-damaging drug resistance through multiple downstream regulations related to RNA and ribosomal metabolism. PI3 may be useful as a biomarker for the therapeutic selection of non-DNA-damaging agents. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Mismatch repair deficiency leads to high mutation rates and microsatellite instability (MSI-H), associated with immune infiltration and responsiveness to immunotherapies. In early stages, MSI-H tumors generally have a better prognosis and lower metastatic potential than microsatellite-stable (MSS) tumors, especially in colorectal cancer. However, in advanced stages, MSI-H tumors lose this survival advantage for reasons that remain unclear. We developed a syngeneic mouse model of MSI cancer by knocking out the MMR gene Msh2 in the metastatic 4T1 breast cancer cell line. This model mirrored genomic features of MSI-H cancers and showed reduction in metastatic incidence compared to their MSS counterparts. In MSI-H tumors, we observed an enrichment of immune gene-signatures that negatively correlated with metastasis incidence. A hybrid epithelial-mesenchymal signature, related to aggressiveness was detected only in metastatic MSI-H tumors. Interestingly, we identified immature myeloid cells at primary and metastatic sites in MSI-H tumor-bearing mice, suggesting that MMR deficiency elicits specific immune responses beyond T-cell activation.

Peritoneal surface malignancies (PSMs) represent a biologically diverse group of cancers that range from primary peritoneal mesothelioma to metastatic gastrointestinal cancers. Because of the heterogenous nature of PSM, there is a large gap in molecular characterization of these cancers. This article reviews the underlying molecular and genetic mechanisms for PSM.

This study aimed to develop a predictive model for the microsatellite-stable (MSS)/epithelial-to-mesenchymal transition (EMT) subtype of gastric cancer (GC) using computed tomography (CT) radiomics and clinicopathological factors.

This retrospective study included 418 patients with GC who underwent primary resection and transcriptome analysis with microarray between October 1995 and May 2008. Using preoperative CT images, radiomic features from the volume of interest in the portal venous phase images were extracted. The patient data were randomly divided into training (70%) and testing (30%) datasets. Optimal radiomics features were selected through a thorough feature-selection process. The final radiomic and clinicopathological factors were selected using a stepwise variable selection method. The area under the curve (AUC) was calculated to evaluate performance.

Seventy patients had EMT subtype GC, and 348 patients had non-EMT subtype based on transcriptome analysis. There were 276 men (66.0 %), with a median age of 59 years (interquartile range: 50-67). Eleven radiomic features were selected for the prediction model using the combined variance inflation factor (VIF) and least absolute shrinkage and selection operator (LASSO) method. A CT radiomics-based prediction model was constructed using logistic regression with AUCs of 0.824 and 0.736 for training and testing, respectively. When clinicopathological factors such as age, tumor size, signet ring cell histology, and Lauren classification were combined, the AUCs of the models increased to 0.849 and 0.840 for training and testing, respectively (p < 0.001 for testing).

A prediction model using CT radiomics and clinicopathological factors showed good performance in predicting the EMT subtype of GC.

Diffuse-type gastric cancer (GC) is closely associated with genetic abnormalities; however, its exact pathological mechanisms are still not understood. It manifests without symptoms before advanced stages and is often difficult to diagnose using routine imaging tests. Therefore, specific targeted therapies for diffuse GC are currently unavailable. In this study, the extract of Pseudolysimachion pusanensis, which is endemic to Korea, inhibited the proliferation of GC cells, MKN1 and SNU668, while the other extracts of the two endemic Pseudolysimachion species did not show any activity. This led to the molecular networking analysis of Pseudolysimachion species to identify the molecules mostly observed only in P. pusanensis. Thirteen new (1-13) and eight known (14-21) compounds were obtained and structurally characterized. Of these, cucurbitacin derivative compounds 1 and 14-16 showed activity, and particularly, the IC50 value of compound 1 was 0.65 and 0.21 μM. Ki-67 expression analysis, single-cell originated cell proliferation assay, and western blot analysis of apoptotic cell death-related molecules revealed that compound 1 mediated both cytostasis and cellular death via apoptosis. Particularly, this compound exhibited an anti-tumorigenic effect on the invasion of diffuse-type GC cells by perturbing the epithelial-to-mesenchymal transition (EMT) pathway, as demonstrated by invasion assays using both 2D models and in vivo-like 3D spheroid co-culture models, as well as western blot analysis of EMT markers. In addition, some functional groups that may or may not be necessary for the activity of cucurbitacin derivatives were identified, and some clues that the presence of metal ions may affect the activity were provided.

Cisplatin (CDDP) based chemotherapy has emerged as the predominant therapeutic regimen for patients with advanced gastric cancer (GC). However, its efficacy is dampened by the development of chemoresistance, which results in poor prognosis of patients. GLI2, a key transcription factor in the Hedgehog (Hh) signaling pathway, is regarded as a target for cancer therapy. However, the significance of GLI2 for CDDP resistance in GC has not been well established. Here, we show that GLI2 expression was upregulated in EMT-type GC and associated with poor prognosis. GLI2 promotes proliferation, migration, and CDDP resistance of GC cells by inducing EMT. In terms of mechanism, GLI2 binds to the promoter region of DEC1 and enhances its expression, thereby co-transcriptionally regulating ZEB1 expression. Animal experiments have demonstrated that both GLI2 knockdown and GLI2 inhibitor significantly enhance CDDP sensitivity in GC. Our data not only identify a novel GLI2/DEC1/ZEB1/EMT pathway in GC CDDP resistance but also provide novel strategies to treat GC in the future.

This study aims to establish a Bayesian network risk prediction model for gastric cancer using data mining methods. It explores both direct and indirect factors influencing the incidence of gastric cancer and reveals the interrelationships among these factors.

Data were collected from early cancer screenings conducted at the People's Hospital of Lincang between 2022 and 2023. Initial variable selection was performed using Least Absolute Shrinkage and Selection Operator (Lasso) and Sliding Windows Sequential Forward Selection (SWSFS), and the screened variables and demographic characteristics features were used as variables for constructing the Bayesian network (BN) model. Subsequently, the performance of the models was evaluated, and the optimal model was selected for network mapping and Bayesian inference using the best model.

The incidence rate of gastric cancer in this region's high-risk population was determined to be 7.09%. The BN model constructed from the set of variables consisting of Lasso's selection variables and demographic characteristics had better performance. A total of 12 variables were incorporated into the BN model to form a network structure consisting of 13 nodes and 18 edges. The model shows that age, gender, ethnicity, current address, upper gastrointestinal symptoms (nausea, acid reflux, vomiting), alcohol consumption, smoking, SGIM gastritis, and family history are important risk factors for gastric cancer development.

The Bayesian network model provides an intuitive framework for understanding the direct and indirect factors contributing to the early onset of gastric cancer, elucidating the interrelationships among these factors. Furthermore, the model demonstrates satisfactory predictive performance, which may facilitate the early detection of gastric cancer and enhance the levels of early diagnosis and treatment among high-risk populations.

Gastric cancer is an inflammation-driven disease often associated with a bad prognosis. Upstream stimulatory factors USF1 and USF2 are pleiotropic transcription factors, with tumor suppressor function. Low expression of USF1 is associated with low survival in gastric cancer patients. USF1 genetic polymorphism -202G > A has been associated with cancer susceptibility. Our aim was to investigate USF1 gene polymorphism and serum level with the risk of gastric cancer.

USF1-202 G/A polymorphism was analyzed by sanger sequencing, with the measure of USF1/USF2 serum levels by ELISA in H. pylori-positive patients with chronic gastritis, gastric precancerous lesions, gastric cancer and in healthy controls.

Our results show that the presence of the USF1-202 A allele increased the risk of gastric cancer compared to G (OR = 2; 95% CI 1.07-3.9; P = 0.02). Genotypically and under the dominant mutation model, the combined USF1- GA/AA -202 genotypes corresponded to higher risk of gastric cancer (OR = 3.5; 95% CI 1.4-8.2; p-value = 0.005) than the GG genotype. Moreover, the G/A transition at USF1-202 was associated with lower USF1 serum level, and mostly observed in gastric cancer patients where the average serological level of USF1 were 2.3 and twofold lower for the AA and GA genotypes, respectively, compared to GG.

USF1-202 G/A polymorphism constitutes a gastric cancer genetic risk factor. Together with USF1/USF2 serum level, they can be proposed as promising biomarkers for gastric cancer detection/prevention.

Gastric adenocarcinoma (GAC) imposes a considerable global health burden. Molecular profiling of GAC from the tumor microenvironment perspective through a multi-omics approach is eagerly awaited in order to allow a more precise application of novel therapies in the near future.

To better understand the tumor-immune interface of GAC, we identified an internal cohort of 82 patients that allowed an integrative molecular analysis including mutational profiling by whole-exome sequencing, RNA gene expression of 770 genes associated with immune response, and multiplex protein expression at spatial resolution of 34 immuno-oncology targets at different compartments (tumorous cells and immune cells). Molecular findings were validated in 595 GAC from the TCGA and ACRG external cohorts with available multiomics data. Prediction of response to immunotherapies of the discovered immunophenotypes was assessed in 1039 patients with cancer from external cohorts with available transcriptome data.

Unsupervised clustering by gene expression identified a subgroup of GAC that includes 52% of the tumors, the so-called Inflamed class, characterized by high tumor immunogenicity and cytotoxicity, particularly in the tumor center at protein level, with enrichment of PIK3CA and ARID1A mutations and increased presence of exhausted CD8+ T cells as well as co-inhibitory receptors such as PD1, CTLA4, LAG3, and TIGIT. The remaining 48% of tumors were called non-inflamed based on the observed exclusion of T cell infiltration, with an overexpression of VEGFA and higher presence of TP53 mutations, resulting in a worse clinical outcome. A 10-gene RNA signature was developed for the identification of tumors belonging to these classes, demonstrating in evaluated datasets comparable clinical utility in predicting response to current immunotherapies when tested against other published gene signatures.

Comprehensive immunophenotyping of GAC identifies an inflamed class of tumors that complements previously proposed tumor-based molecular clusters. Such findings may provide the rationale for exploring novel immunotherapeutic approaches for biomarker-enriched populations in order to improve GAC patient's survival.

Immunotherapy has surfaced as a promising therapeutic modality for gastric cancer (GC). A comprehensive review of advancements, current status, and research trends in GC immunotherapy is essential to inform future investigative efforts.

To delineate the trends, advancements, and focal points in immunotherapy for GC.

We performed a bibliometric analysis of 2906 articles in English concerning GC immunotherapy published from 2000 to December 20, 2023, indexed in the Web of Science Core Collection. Data analysis and visualization were facilitated by CiteSpace (6.1.6R), VOSviewer v.1.6.17, and GraphPad Prism v8.0.2.

There has been an increase in the annual publication rate of GC immunotherapy research. China leads in publication volume, while the United States demonstrates the highest citation impact. Fudan University is notable for its citation frequency and publication output. Co-citation analysis and keyword frequency revealed and highlighted a focus on GC prognosis, the tumor microenvironment (TME), and integrative immunotherapy with targeted therapy. Emerging research areas include gastroesophageal junction cancer, adoptive immunotherapy, and the role of Treg cell in immunotherapy.

GC immunotherapy research is an expanding field attracting considerable scientific interest. With the clinical adoption of immunotherapy in GC, the primary goals are to enhance treatment efficacy and patient outcomes. Unlike hematological malignancies, GC's solid TME presents distinct immunological challenges that may attenuate the cytotoxic effects of immune cells on cancer cells. For instance, although CAR-T therapy is effective in hematological malignancies, it has underperformed in GC settings. Current research is centered on overcoming immunosuppression within the TME, with a focus on combinations of targeted therapy, adoptive immunotherapy, Treg cell dynamics, and precise prognosis prediction in immunotherapy. Additionally, immunotherapy's role in treating gastroesophageal junction cancer has become a novel research focus.

Gastric cancer (GC) is a highly heterogeneous tumour with high morbidity. Approximately 95% of GC cases are gastric adenocarcinomas, which are further categorized into two predominant subtypes: diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC). These subtypes exhibit distinct pathophysiological and molecular characteristics, reflecting their unique tumorigenic mechanisms.

In this study, we employed a comprehensive approach to identify driver genes associated with DGC and IGC by focusing on copy number variation (CNV) genes within the competing endogenous RNA (ceRNA) network. The influence of driver CNV genes on the molecular, cellular, and clinical differences between DGC and IGC was subsequently analysed. Finally, therapeutic strategies for DGC and IGC were evaluated based on the status and functional pathways of the driver CNV genes.

A total of 17 and 22 driver CNV genes were identified in DGC and IGC, respectively. These genes drive subtype differences through the ceRNA network, resulting in alterations in the tumour microenvironment (TME). Based on these differences, personalized treatment strategies for DGC or IGC could be developed. Immune checkpoint inhibitors may be an effective treatment option in IGC. Additionally, DGC patients with homozygous deletion of PPIF might benefit from adjuvant chemotherapy, whereas those with high-level amplification of MTAP could respond to targeted therapy.

Driver CNV genes were identified to reveal the underlying cause of heterogeneity in DGC and IGC. Furthermore, specific driver CNV genes were identified as potential therapeutic targets, facilitating personalized treatment.

The incidence of gastroesophageal cancers is rising, driven, in part, by an increasing burden of risk factors of obesity and gastroesophageal reflux. Despite efforts to address these risk factors, and a growing interest in methods of population screening, the bulk of these tumours are unresectable at diagnosis. In this setting, effective systemic treatments are paramount to improve survival and quality of life. Early and accurate identification of oncogenic drivers, such as human epidermal growth factor receptor 2 (HER2), present in 5-30% of gastroesophageal adenocarcinomas (GEAs), is integral to guide choice of therapies due to the clear predictive implications that arise from overexpression of this receptor. After trastuzumab, the first anti-HER2 agent with approved use in HER2-positive GEA, the addition of pembrolizumab to first-line trastuzumab-chemotherapy and trastuzumab deruxtecan in the refractory space have more recently changed practice. Yet, the response to these agents has been vastly different across patients with HER2-positive disease, underpinning the need for reliable biomarkers of response. Emergent data have suggested that levels of HER2 expression on tissue or liquid biopsies may predict response to first-generation HER2 therapies while HER2 heterogeneity, receptor changes, co-occurring molecular alterations and oncogenic genomic and metabolic reprogramming may be implicated in resistance. A robust knowledge of the mechanisms of resistance and response to HER2-directed therapies is necessary to inform novel strategies of HER2-targeting and guide choice combinations with other biomarker-directed therapies, to improve outcomes from a new generation of clinical trials in HER2-positive GEA. Understanding and close examination of previous failures in this space form an important part of this assessment, as does correlative biomarker and translational work pertaining to the role of HER2 and dynamic changes that result through treatment exposure. In this review, we aim to provide an overview of strategies for HER2 targeting, summarising both the successes and disappointments in this therapeutic landscape and discuss existing challenges and future perspectives on development in this highly morbid tumour type.

Lipid rafts are highly heterogeneous and dynamic microdomains involved in molecule trafficking and signaling transduction. This study investigates the role of lipid rafts in gastric cancer and their key regulators. Analyzing FFPE samples from 111 gastric cancer patients, we found that high lipid raft levels predict poor prognosis. Modulating these levels in gastric cancer cell lines significantly impacted cell proliferation, migration, and invasion. Weighted Gene Co-expression Network Analysis identified AXL as a hub gene associated with lipid rafts. AXL knockdown experiments revealed its interaction with Caveolin-1, a caveolae lipid raft protein, which regulates lipid raft levels and promotes AKT and ERK signaling, enhancing cancer development and metastasis. In vivo tumorigenesis assays and survival analyses further supported these findings. This study underscores the significance of lipid rafts in gastric cancer and identifies AXL as a novel regulator, offering new insights into the molecular mechanisms of cancer progression and suggesting potential therapeutic targets.

Cancer, a heterogeneous disease, presents significant challenges for drug development due to its complex etiology. Drug repurposing, particularly through network medicine approaches, offers a promising avenue for cancer treatment by analyzing how drugs influence cellular networks on a systemic scale. The advent of large-scale proteomics data provides new opportunities to elucidate regulatory mechanisms specific to cancer subtypes. Herein, we present NetSDR, a Network-based Subtype-specific Drug Repurposing framework for prioritizing repurposed drugs specific to certain cancer subtypes, guided by subtype-specific proteomic signatures and network perturbations. First, by integrating cancer subtype information into a network-based method, we developed a pipeline to recognize subtype-specific functional modules. Next, we conducted drug response analysis for each module to identify the "therapeutic module" and then used deep learning to construct weighted drug response network for the particular subtype. Finally, we employed a perturbation response scanning-based drug repurposing method, which incorporates dynamic information, to facilitate the prioritization of candidate drugs. Applying the framework to gastric cancer, we attested the significance of the extracellular matrix module in treatment strategies and discovered a promising potential drug target, LAMB2, as well as a series of possible repurposed drugs. This study demonstrates a systems biology framework for precise drug repurposing in cancer and other complex diseases.

Microsatellite instability (MSI)-high tumors represent a distinct, small-fraction subtype in esophagogastric junction cancer or gastric cancer (GC), yet their clinical significance remains poorly understood. This study aimed to investigate the prevalence and clinicopathological features of chemotherapy-naïve metastatic or recurrent MSI-high GC as a prescreening study for a phase II trial of nivolumab plus ipilimumab.

Key inclusion criteria included metastatic or recurrent adenocarcinoma of GC, ECOG performance status of 0 or 1, and no prior systemic therapy for metastatic or recurrent disease. MSI status was tested using multiplex PCR fragment analysis (MSI Testing Kit, FALCO). The primary endpoint was the prevalence of MSI-high GC.

Between October 2020 and October 2022, 930 eligible patients from 75 centers in Japan were analyzed. The prevalence of MSI-high GC was 5.6% (95% CI 4.2-7.3). MSI-high GC was more frequently observed in females than males (9.6% vs 3.8%, p < 0.001), patients aged ≥ 70 years compared to those < 70 years (8.0% vs 2.8%, p < 0.001), in the lower stomach than other locations (10.5% vs 3.2%, p < 0.001), HER2-negative tumors than HER2-positive tumors (6.5% vs 1.8%, p = 0.02), and in patients without liver metastasis than those with liver metastasis (6.9% vs 2.2%, p = 0.004).

The prevalence of MSI-high tumors among chemotherapy-naïve patients with unresectable GC was 5.6%. These tumors were associated with female sex, older age, lower stomach, HER2-negative, and absence of liver metastasis. These findings would help assuming MSI-high tumors and may have significant implications for clinical practice and studies targeting this GC subtype.

In less than a decade, immune checkpoint inhibitors (ICIs) have transformed the management of mismatch repair-deficient (dMMR) and microsatellite instability-high (MSI) cancers. However, beyond colorectal cancer (CRC), much of the evidence is mostly derived from non-randomized phase II studies or post-hoc analyses of broader clinical trials. dMMR/MSI tumours represent a specific subgroup of gastro-esophageal adenocarcinomas (GEA), accounting for approximately 9 % of cases, with a higher prevalence in early-stage compared to advanced-stage disease and older female patients. These tumours are predominantly sporadic, often linked to MLH1 promoter methylation, and rarely exhibit HER2 overexpression/ERBB2 amplification or other oncogenic drivers. The treatment landscape for early stage dMMR/MSI GEA is likely to change substantially soon, as ICIs have shown high pathological complete response (pCR) rates in small phase II trials, raising questions on optimisation of neoadjuvant therapy, and paving the way for organ preservation. The standard of treatment for untreated patients with advanced dMMR/MSI GEA is chemotherapy + ICI irrespectively of PDL-1 status. However, the role of chemotherapy-free regimen consisting of CTLA-4 plus PD-1 inhibitors remains undetermined. This review addresses these and other emerging questions, offering expert opinions and insights into the future therapeutic landscape for dMMR/MSI GEA.

Gastric cancer (GC) burden is currently evolving with regional differences associated with complex behavioural, environmental, and genetic risk factors. The LEGACy study is a Horizon 2020-funded multi-institutional research project conducted prospectively to provide comprehensive data on the tumour biological characteristics of gastroesophageal cancer from European and LATAM countries.

Treatment-naïve advanced gastroesophageal adenocarcinoma patients were prospectively recruited in seven European and LATAM countries. Formalin-fixed paraffin-embedded primary tumour endoscopic biopsy samples were collected and submitted for central morphological and immunohistochemical characterization and TP53 molecular assessment and Helicobacter pylori infection.

A total of 259 patients were included in the study: 137 (53%) from LATAM and 122 (47%) from Europe. Significant biological differences were detected between European and LATAM patients. Low representation of chromosomal instability (CIN) and HER2 positive cases were found in LATAM. MUC6 and PD-L1 were more frequently overexpressed in European cases, showing a significant correlation across the entire study population, with this association being especially pronounced in MMRdeficient cases. Both TP53 mutation by next-generation sequencing and p53 immunohistochemical aberrant pattern were linked with features associated with chromosomal instability. No regional differences were observed in H. pylori prevalence or abundance, indicating that the afore mentioned variations cannot be attributed to this factor.

Our findings underscore a need for region-specific approaches in gastroesophageal cancer diagnosis and treatment. MUC6 emerges as a putative immune regulator that needs further investigation. Research tailored to the unique biological profiles in different global regions is crucial to effectively address the observed disparities.

Emerging evidence indicates that the transcription factor Yin Yang 1 (YY1) plays a critical role in the carcinogenesis and progression of various human malignancies. YY1 is highly expressed in gastric cancer (GC), raising interest in its role in GC.

This study aims to analyze the role of YY1 in gastric cancer, investigate its effect on the tumor microenvironment, and assess its potential as a prognostic marker.

Transcriptomic data and clinical information from GC patients were obtained from the TCGA and UCSC databases. YY1 expression was analyzed using the R "limma" package. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed with the online tool clusterProfiler. The relationship between YY1 expression levels and the tumor microenvironment was examined in different risk groups of GC patients. Additionally, YY1-positive staining in 26 clinical GC samples was measured using ImageJ software. Co-expression analysis was used to identify prognostic genes associated with YY1, and a prognostic risk model was built and optimized. Results showed that YY1 was significantly overexpressed in 415 GC (p < 0.001) and was associated with poorer survival outcomes (p = 0.043). GO and KEGG showed that YY1 was involved in key biological processes of the disease. Higher YY1 expression was correlated with lower stromal and immune cell content in the tumor microenvironment. Immunohistochemical staining confirmed YY1 overexpression in GC tissues compared to normal tissues (p = 0.0293). Positive correlations were observed between YY1 and the genes MTA1, TTL15, HNRNPU, WDR20, and PPP4R3A. The prognostic model, which included genes significantly associated with YY1 (risk score AUC = 0.690), predicted patient survival better than other clinical variables.

These findings suggest that YY1 plays an important role in the development of GC. Targeting the YY1 pathway may be a potential treatment strategy for GC.

Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.

GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi). Hierarchical clustering identified clusters with distinct survival outcomes, and differentially expressed genes (DEGs) between clusters were identified. Weighted Gene Co-expression Network Analysis (WGCNA) identified modules and hub genes associated with clinical traits. Overlapping DEGs and hub genes underwent functional enrichment, protein-protein interaction (PPI) network analysis, and survival analysis. A prognostic decision tree was constructed using survival-associated shared genes.

Hierarchical clustering identified six clusters among 375 TCGA GC patients, with significant survival differences between cluster 1 (low hypoxia, high stemness) and cluster 4 (high hypoxia, high stemness). Validation in the GSE62254 dataset corroborated these findings. WGCNA revealed modules linked to clinical traits and survival, with functional enrichment highlighting pathways like cell adhesion and calcium signaling. The decision tree, based on genes such as AKAP6, GLRB, and RUNX1T1, achieved an AUC of 0.81 (training) and 0.67 (test), demonstrating the utility of combined scores in patient stratification.

This study introduces a novel hypoxia-stemness-based prognostic decision tree for GC. The identified genes show promise as prognostic biomarkers, warranting further clinical validation.

Gastric cancer (GC) is recognized for intrinsic heterogeneity, although it is similarly approached in Europe and Latin America (LATAM). The LEGACY project aimed to deepen GC molecular understanding through multi-omics analysis in Europe and LATAM GC samples.

Tumor samples were centrally reviewed for histology, human epidermal growth factor receptor 2 (HER2) expression, and mismatch repair-deficient (dMMR)/microsatellite instability (MSI) status. In addition, we assessed Epstein-Barr virus (EBV) status, programmed death-ligand 1 (PD-L1) combined positive score (CPS), and carried out tissue genomic profiling including tumor mutation burden (TMB) quantification plus targeted transcriptomics for immune microenvironment and cancer cell signaling scores.

In total, 328 GC patients were enrolled. HER2-positive GC and high PD-L1 CPS were more frequent in Europe than in LATAM (9% versus 3% and 15% versus 3%, respectively), whereas EBV was mainly found in LATAM (7%, versus 3% in Europe), and dMMR/MSI tumors were equally distributed (16%). High TMB was enriched in dMMR/MSI and EBV tumors. Mutations in homologous recombination repair (HRR) genes were frequent in both cohorts (24.8% and 14.7% in Europe and LATAM, respectively), and mostly found in dMMR/MSI (63.6%) and intestinal HER2-negative (18.7%) tumors. The prognosis was poor in diffuse HER2-negative GC patients, whose tumors presented an immunosuppressive microenvironment and other distinct pathway activation signatures.

Our findings relate specific molecular alterations of GC tumors from Europe and LATAM to actionable biomarkers for precision cancer therapies. The proposed GC stratification can be implemented in routine care and guide drug development strategies.

Gastric cancer (GC) is among the most lethal malignancies worldwide. Due to the substantial heterogeneity of GC, more accurate molecular typing systems are desperately required to enhance the prognosis of GC patients.

The major immune cell subclusters in GC were identified by a single-cell RNA sequencing (scRNA-seq) dataset. High-dimensional weighted gene coexpression network analysis (hdWGCNA) and multiple bioinformatics methods were utilized to classify the molecular subtypes of GC and further investigate the differences among the subtypes. Based on the module genes and differentially expressed genes (DEGs), random survival forest analysis was applied to identify the key prognostic genes for GC, and the roles and functional mechanisms of the key genes in GC were explored by clinical samples and cellular experiments.

Two distinct GC molecular subtypes (C1 and C2) associated with neutrophils were identified, with C1 associated with better prognosis. Compared with C2 subtype, C1 subtype has significant differences in immune infiltration, immune checkpoint expression, signaling pathway regulation, tumor mutation burden, and immunotherapy and chemotherapeutic drug sensitivity. Three new key genes (VIM, RBMS1 and RGS2) were revealed to be highly correlated with the prognosis of GC patients. In addition, the expression and cellular functions of key genes RBMS1 and RGS2 in gastric carcinogenesis were verified.

We identified two neutrophil-related molecular GC subtypes with different prognostic outcomes and clinical significance. VIM, RBMS1 and RGS2 were identified as potential prognostic markers and therapeutic targets for GC. These findings provide a new perspective for the molecular typing and personalized treatment of GC.

Gastric cancer (GC) commonly presents in advanced stages with metastatic spread to the peritoneal cavity, and outcomes associated with gastric cancer with peritoneal metastasis (GCPM) continue to carry a dismal prognosis. Persistent challenges in the detection of peritoneal metastasis (PM) have resulted in a relative paucity of high-quality data to inform management decisions. Several consensus groups have published recommendations to guide management, including most recently the National Comprehensive Cancer Network guidelines, which now include cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) as a potential treatment modality in select patients with GCPM. Multiple clinical trials have investigated the use of CRS/HIPEC and other peritoneal-directed therapies, such as intraperitoneal chemotherapy (IPC) and pressurized intraperitoneal aerosolized chemotherapy (PIPAC). As high-volume centers work to incorporate such therapies into their practice, ongoing clinical trials are aimed at understanding their efficacy. Recent findings have improved understanding of the mechanisms and pathophysiology underlying GCPM while the discovery of novel targets offers potential for drug development and therapeutic strategies to overcome treatment resistance. This review highlights recent advancements and addresses the persistent challenges in managing GCPM while also offering a comprehensive summary of current guidelines and treatment strategies.

Cancers represent a significant global health burden, affecting millions of individuals each year [...].

Gastric cancer (GC) is one of the most common causes of cancer-related death worldwide. As a novel form of programmed cell death, disulfidptosis is characterized by excessive cysteine accumulation, disulfide stress and actin destruction. There is evidence that targeting disulfidptosis is a promising anticancer strategy. Further improvement of GC risk stratification based on disulfidptosis has positive clinical significance.

We analyzed the expression levels of disulfidptosis-associated genes (DPAGs) in normal and GC tissues and characterized the molecular subtypes of GC patients. Based on the characteristics of DPAG subtypes, differentially expressed prognosis-related genes were selected by LASSO-univariate Cox analysis and multivariate Cox analysis analyzed to establish a prognostic model. Using single-cell sequencing analysis reveals the cell subpopulation for GC. The function of the selected target in GC was verified by in vitro experimental means, including siRNA, qRT-PCR, Western blot, CCK-8, and Transwell assay.

DPAG score was verified to be an independent prognostic factor of GC and was significantly associated with poor prognosis of gastric cancer. Subsequent studies on subgroup immunoinfiltration characteristics, drug sensitivity analysis, immunotherapy response and somatic mutation characteristics of DPAG score comprehensively confirmed the potential guiding significance of DPAG score for individualized treatment of gastric cancer patients. Single-cell sequencing analysis revealed the expression characteristics of DPAG-related prognostic signatures across cell subpopulations. In vitro experiments showed APC11, as one of the selected DPAGs, was highly expressed in gastric cancer, and knockdown of APC11 could significantly inhibit the proliferation and migration of GC cells, demonstrating the reliability of bioinformatics results.

The results of this study provide a new perspective for exploring the role of disulfidptosis in the occurrence and development of GC.

High heterogeneity in gastric cancer (GC) remains a challenge for standard treatments and prognosis prediction. Dysregulation of sialic acid metabolism (SiaM) is recognized as a key metabolic hallmark of tumor immune evasion and metastasis. Herein, we aimed to develop a SiaM-based metabolic classification in GC.

SiaM-related genes were obtained from the MsigDB database. Bulk and single-cell transcriptional data of 956 GC patients were acquired from the GEO, TCGA, and MEDLINE databases. Proteomic profiles of 20 GC samples were derived from our institution. The consensus clustering algorithm was applied to identify SiaM-based clusters. The SiaM-based model was established via LASSO regression and evaluated via Kaplan‒Meier curve and ROC curve analyses. In vitro and in vivo experiments were conducted to explore the function of ST3GAL1 in GC.

Three SiaM clusters presented distinct patterns of clinicopathological features, transcriptomic alterations, and tumor immune microenvironment landscapes in GC. Compared with clusters A and B, cluster C presented elevated SiaM activity, higher metastatic potential, more abundant immunosuppressive features, and a worse prognosis. Based on the differentially expressed genes between these clusters, a risk model for six genes (ARHGAP6, ST3GAL1, ADAM28, C7, PLCL1, and TTC28) was then constructed. The model exhibited robust performance in predicting peritoneal metastasis and prognosis in four independent cohorts. As a hub gene in the model, ST3GAL1 promoted GC cell migration and invasion in vitro and in vivo.

Our study proposed a novel SiaM-based classification that identified three metabolic subtypes with distinct characteristics of tumor microenvironment and clinical outcomes in GC.

This study aims to develop a simple, clinically applicable classification system to predict pCR based on carcinoembryonic antigen (CEA) trajectory during NAC.

This study included 366 AGC patients who received NAC followed by radical gastrectomy. CEA levels were measured before, during, and after NAC, with changes classified into three trajectory types: Type I (>=80% decline), Type II (>=40% but <80% decline), and Type III (<40% decline or increase). We analyzed associations between these CEA trajectories, pCR, lymph node remission, and survival.

pCR was achieved in 10.4% (38/366) of patients. pCR rates were significantly higher in Type I (41%) and Type II (15.8%) trajectories compared to Type III (6.7%). Lymph node remission also correlated with CEA trajectories, with Type I having the highest proportion of ypN0 (79.2%). Multivariate analysis identified CEA trajectory subtypes and tumor differentiation as independent predictors of pCR. This classification system proved robust across subgroups. Although no significant differences in overall survival were observed between subtypes, higher initial CEA levels were associated with worse survival.

The trajectory of CEA change during NAC is a promising predictor of pCR in AGC. This simple and accessible classification system may facilitate personalized surgical strategies for patients with AGC.

Alpha-fetoprotein-producing gastric carcinoma (AFPGC) is a rare and aggressive subtype of gastric cancer (GC). A comprehensive analysis of clinicopathological features, immunophenotypes, molecular characteristics, and survival in AFPGC contributes to identifying potential therapeutic targets and developing new strategies to manage this disease. A retrospective cohort study was conducted at Shanxi Cancer Hospital from January 2018 to December 2020, involving patients diagnosed with GC and elevated AFP serum levels. Among these, 91 patients underwent immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and next-generation sequencing (NGS) to reveal the immunophenotypic and molecular characteristics of AFPGC. We found that AFPGC is more common in males and primarily occurs in the cardia and antrum of the stomach. A panel of IHC markers including AFP, GPC3, SALL4, CD10, CDX-2, and ATBF1 can be used for the diagnosis and differentiating AFPGC. NGS analysis revealed that TP53 hypermutation was the most frequent molecular event associated with AFPGC. The altered signaling pathways included disease signal transduction, receptor tyrosine kinase signaling and intracellular second messenger signaling pathways. The cumulative incidence of 21 genes, based on the evidence of clinical actionability in the OncoKB, was found to be 59.34%. Among these genes, CCNE1, ERBB2, and EGFR were the most frequently observed. This underscores the potential benefit of targeted therapy for patients with AFPGC. Furthermore, LRP1B and ARID1A have been identified as prognostic factors associated with overall survival (OS) and disease-free survival (DFS), respectively. Our results aim to improve AFPGC diagnosis by identifying potential therapeutic targets and prognostic factors, which could help facilitate the development of new treatment strategies.

The elevation of IQGAP3 expression in diverse cancers indicates a key role for IQGAP3 in carcinogenesis. Although IQGAP3 was established as a proliferating stomach stem cell factor and a regulator of the RAS-ERK pathway, how it drives cancer growth remains unclear.

We define the function of IQGAP3 in gastric cancer (GC) development and progression.

We studied the phenotypic changes caused by IQGAP3 knockdown in three molecularly diverse GC cell lines by RNA-sequencing. In vivo tumorigenesis and lung metastasis assays corroborated IQGAP3 as a mediator of oncogenic signalling. Spatial analysis was performed to evaluate the intratumoral transcriptional and functional differences between control tumours and IQGAP3 knockdown tumours.

Transcriptomic profiling showed that IQGAP3 inhibition attenuates signal transduction networks, such as KRAS signalling, via phosphorylation blockade. IQGAP3 knockdown was associated with significant inhibition of MEK/ERK signalling-associated growth factors, including TGFβ1, concomitant with gene signatures predictive of impaired tumour microenvironment formation and reduced metastatic potential. Xenografts involving IQGAP3 knockdown cells showed attenuated tumorigenesis and lung metastasis in immunodeficient mice. Accordingly, immunofluorescence staining revealed significant reductions of TGFβ/SMAD signalling and αSMA-positive stromal cells; digital spatial analysis indicated that IQGAP3 is indispensable for the formation of two phenotypically diverse cell subpopulations, which played crucial but distinct roles in promoting oncogenic functions.

IQGAP3 knockdown suppressed the RAS-TGFβ signalling crosstalk, leading to a significant reduction of the tumour microenvironment. In particular, IQGAP3 maintains functional heterogeneity of cancer cells to enhance malignant growth. IQGAP3 is thus a highly relevant therapy target in GC.

This review addresses the current treatment paradigm and new advancements in the management of microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) esophagogastric cancer (EGC).

While chemotherapy and surgery remain the cornerstone of EGC treatment, MSI-H/dMMR tumors harbor high tumor mutational burden and represent a subset of patients who benefit from immune checkpoint inhibitors (ICI). ICI has been incorporated in the front line setting with and without chemotherapy for advanced disease. Recently, ICI has been studied in the perioperative setting for resectable disease. Though perioperative ICI results in improved response rates, it is not yet clear whether this translates to a survival benefit. Despite high response rates with ICI in this patient population, many do not respond to therapy, representing a major challenge in treatment. Preclinical studies have highlighted potential mechanisms of resistance which will guide drug development and clinical trials.

Human tissue samples are essential for translational cancer research. However, less than 20% of current biobank and genomic samples were obtained from minority patients, which may lead to biased understanding of cancer biology. The objective of this study was to identify factors associated with patient enrollment in our institution's gastric cancer biobank.

Patients with suspected or confirmed gastric or gastroesophageal junction cancer undergoing surgical procedures at our institution were invited to enroll in a prospective gastric cancer biobank. We retrospectively reviewed patients who were invited to enroll from 2017 to 2023 at our safety-net and university hospitals. We compared patients who enrolled to those who declined to identify factors that predict enrollment.

Hispanic patients had similar odds of enrollment as non-Hispanic White patients (odds ratio (OR): 1.22, 95% confidence interval (CI): 0.54-2.73, P = 0.63). Non-Hispanic minorities (Black/African Americans and Asians) were less likely to enroll when compared to non-Hispanic Whites (OR: 0.41, 95% CI: 0.18-0.95, P = 0.04). Minority patients treated at our safety-net hospital had higher odds of enrollment than those treated at our university hospital (OR: 2.62, 95% CI: 1.11-5.99, P = 0.02).

Efforts to improve diversity in biomedical research cannot consider minority patients as a monolithic cohort. Instead, targeted interventions that address diverse cultural concerns and improve access to enrollment at safety-net centers are requisite.

Gastric cancer (GC) is a formidable adversary in the field of oncology. The low early diagnosis rate of GC results in a low overall survival rate. Therefore, early accurate diagnosis and effective treatment are the key to reduce the mortality of GC. With the advent of nanotechnology, researchers continue to explore new possibilities for accurate diagnosis and effective treatment. One such breakthrough is the application of DNA nanotechnology. In this paper, the application of exciting DNA nanomaterials in the diagnosis and treatment of GC is discussed in depth. Firstly, the biomarkers related to GC and the diagnostic strategies related to DNA nanotechnology are summarized. Second, the latest research progress of DNA nanomaterials in the GC targeted therapy are summarized. Finally, the challenges and opportunities of DNA nanomaterials in the research and clinical application of GC are prospected.